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cs.CL2026
StudentSim: Training LLM-based Student Simulators
Ke Yang, Chenglong Wang, Michel Galley +4
AI tutors are most useful when they adapt to each student's strengths, weaknesses, and preferred guidance, but evidence about which guidance works for which student is sparse, slow…
cs.CL2026
PlugMem: A Task-Agnostic Plugin Memory Module for LLM Agents
Ke Yang, Zixi Chen, Xuan He +6
Long-term memory is essential for large language model (LLM) agents operating in complex environments, yet existing memory designs are either task-specific and non-transferable, or…
cs.CL2024
Bias and Volatility: A Statistical Framework for Evaluating Large Language Model's Stereotypes and the Associated Generation Inconsistency
Yiran Liu, Ke Yang, Zehan Qi +3
We present a novel statistical framework for analyzing stereotypes in large language models (LLMs) by systematically estimating the bias and variation in their generation. Current…